Deep Learning with Python (Video 9)

The video tutorial explains how to define and implement dense layers in Keras, focusing on the methods and parameters required for layer definition. It covers the initialization of trainable weights, the role of the build method, and the importance of output shape. The tutorial also discusses the use of activation functions and regularization parameters, providing a detailed walkthrough of the dense layer implementation in Keras, with references to the Keras GitHub repository.

What is the role of the activation function in a dense layer?

Explain how the output shape of a dense layer is determined in Keras.

What are the key parameters that need to be defined when initializing a dense layer in Keras?

Describe the process of how weights are initialized in a dense layer.

What is the significance of the 'trainable weights' in a Keras layer?